Triple

T6278363
Position Surface form Disambiguated ID Type / Status
Subject Nick Cannon E140717 entity
Predicate givenName P17 FINISHED
Object Nicholas E28979 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Nicholas | Statement: [Nick Cannon, givenName, Nicholas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nicholas
Context triple: [Nick Cannon, givenName, Nicholas]
  • A. Nicholas chosen
    Nicholas is a masculine given name of Greek origin, commonly used in many cultures and historically borne by numerous saints, rulers, and notable figures.
  • B. Rupert
    Rupert is a masculine given name of Germanic origin, commonly used in English-speaking countries and borne by various notable figures.
  • C. Rupert
    Rupert is a small town located in Greenbrier County in the state of West Virginia, United States.
  • D. Nicholas Van Orton
    Nicholas Van Orton is a wealthy, emotionally detached investment banker whose life unravels after he becomes entangled in a mysterious and elaborate psychological "game" in the film *The Game*.
  • E. Nicolai
    Nicolai is a German surname historically associated with figures such as the Enlightenment-era publisher and writer Friedrich Nicolai.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69c008cc158881908df6ec94a911c736 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c063daec108190859d1d5dbafd5b42 completed March 22, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5194e9b3881908188f004c4a03a09 completed March 26, 2026, 11:32 a.m.
Created at: March 22, 2026, 4:26 p.m.